Coffee Shop Schema - SquarespaceShop+Schema.pdf · SandraSweat&*&1& & The Austin Coffee Shop:...

The Austin Coffee Shop: Schema for a Functional Space

Schema Creation Project: Organizing Information 2015

Sandra Sweat

February 25, 2015

Sandra Sweat -‐ 1

The Austin Coffee Shop: Schema for a Functional Space

There is more to a coffee shop than simply serving coffee and providing wifi for the

masses. Coffee shops have created identities that draw customers into the store and keep them

coming back. Some shops serve food and alcohol, others have comfy couches and extended

hours, and some have inexpensive coffee—all attributes that contribute to a shop’s identity. The

identity of a coffee shop helps customers decide which shop fits their needs.

For this schema, the intended audience is students whose goal is to locate a space for

either individual or group study sessions. Some considerations for groups include:

accommodations for the size of the group, seating for all members during peak hours, and the

fact that some group members require a beer after group meetings. Considerations for

individuals include food offerings for extended sessions, coffee choices, and the least busy times

of day.

What is a coffee shop?

First, the coffee shop must have its origins in Austin. It cannot be part of a chain or

franchise that was started elsewhere. Next, and only marginally less important, a coffee shop

serves coffee. For this schema, a coffee shop must sell a minimum of five coffee beverages,

where a coffee beverage is a drink made from coffee beans. Examples include espresso-based

drinks (latte, mocha), drip coffee, and iced coffee (thai coffee, blended coffee). Coffee must be

the primary offering at the coffee shop, which may be measured in several ways. One way is the

availability of other products other than coffee—if the shop has five display cases of baked

goods and then offers coffee, then that shop does not qualify as a coffee shop.

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A coffee shop must also be inside a building and have a dedicated space to serve and

prepare coffee. Staff must be dedicated to that area (they may be called a barista, though job

titles are not necessary for inclusion), and in spaces where there are other sales the barista cannot

be replaced by an untrained associate. Lastly, there must be a dedicated cash register for the

coffee shop.

Other requirements include free WiFi available during open hours, indoor seating near

the serving area, and a limited kitchen space. For this schema, coffee shops that sell food are

limited by the following constraints: food must be either a snack or a light meal. A snack is a

single item of food, such as a piece of fruit, bag of chips, or an energy bar. A light meal is a

single dish such as pizza, chips and hummus, a sandwich, a piece of quiche, or a

salad. Consumption of these items must not be the primary purpose for going to the coffee

shop. Other non-coffee items, such as alcohol, must also be limited. The shop may serve beer

or wine, but not mixed drinks.

From these restraints, the following entities are not coffee shops: food trailers that serve

coffee, carts that sell coffee, establishments that focus on lunch or dinner as their primary

offerings, and gas stations that serve coffee. Also, if an establishment stops fulfilling the

requirements of a coffee shop during their hours, they are also not a coffee shop. For instance, if

a business serves primarily coffee from 8am to 5pm and switches off the WiFi at 5pm and starts

serving mixed drinks, then the establishment is not a coffee house.

The central case for this schema is Thunderbird Coffee on Manor (described as the

example) and the border case is the Whole Foods coffee counter at the North Lamar location.

Defined attributes include: name, address, hours, number of coffee beverages served, price for a

Sandra Sweat -‐ 3

large coffee, food, alcohol, building type, WiFi, seating, outdoor space, parking, traffic patterns,

life, and created.

A note on formatting: every attribute has a defined format. The outline precedes the selected attributes for the schema. Attribute Definition: a description of the attribute in the context of the schema. Instruction: how to find or collect the information or notes on entry. Controlled Vocabulary: restricted terms for entry. All terms are lowercase with the exception of the Name attribute value and days of the week. Format: how the values must be entered. Characters represent what type of value should make up the entry. # - integer hh:mm – time in hours and minutes term – refers to controlled vocabulary attribute_term – refers to controlled vocabulary in another attribute Repeatable: yes/no answer only. Yes answers have additional explanation. Example

Attribute value

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Name Definition: the name of the coffee shop. Instruction: The name may be located in the following places: on the coffee shop’s building, the menu of the coffee shop, or on the coffee shop’s website. The name is not an unofficial moniker made by those who go there frequently; it must be the name that the owners display for business. In the case that the coffee shop has multiple locations, the coffee shop’s location is also listed in the name attribute by street name. Each location must be described individually. Controlled Vocabulary: N/A Format: name - street location for shops with multiple locations Repeatable: No Example

Name Thunderbird Coffee - Manor

Name Bennu

Address Definition: the physical street location of the coffee shop. Instruction: the address may be found in a directory of locations, on the coffee shop’s website, or on the shop’s building. The address must include street number, street name, and zip code. Do not list the city and state. Controlled Vocabulary: N/A Format: street number street name, zip code. Repeatable: No Example

Address 2200 Manor Rd., 78722

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Hours Definition: when the shop is open for business. Instruction: listings of hours may be found on the shop’s website, the shop door, or on the menu. Controlled Vocabulary: Time must be listed in standard time and by day. Format: Mon/hh:mm AM-hh:mm PM, Tue/hh:mm AM-hh:mm PM, Wed/hh:mm AM-hh:mm PM, Thurs/hh:mm AM-hh:mm PM, Fri/hh:mm AM-hh:mm PM, Sat/hh:mm AM-hh:mm PM, Sun/hh:mm AM-hh:mm PM.

For 24 hour establishments, the time should be listed as 24 hours/7days. Repeatable: Yes. When new hours occur the old hours shift into a subcategory with the last date of entry at the beginning of the hours list. Example

Hours Mon/06:30 AM-11:30 PM, Tue/06:30 AM-11:30 PM, Wed/06:30 AM-11:30 PM, Thurs/06:30 AM-11:30 PM, Fri/06:30 AM-11:30 PM, Sat/07:30 AM-11:00 PM, Sun/07:30 AM-11:00 PM

Hours 2013-02-22: Mon/08:00 AM-11:30 PM, Tue/08:00AM-11:30 PM, Wed/08:00AM-11:30 PM, Thurs/08:00AM-11:30 PM, Fri/08:00 AM-11:30 PM, Sat/08:30 AM-11:00 PM, Sun/08:30 AM-11:00 PM

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Number of Coffee Beverages Served

Definition: drinks that contain some amount of coffee or espresso. Instruction: count items of the menu that have coffee or espresso. Example include, but are not limited to: coffee, espresso, macchiato, americano, cappuccino, latte, mocha, french press, pour over, iced coffee, cafe au lait, and thai iced coffee. Multiple listed instances of latte count as multiple beverages. However, the items must be listed on the menu and do not count unlisted customer or barista creations. Controlled Vocabulary: N/A Format: # Repeatable: Yes. When the number of beverages changes the value shift into a subcategory with the last date of entry at the beginning of the list. See Hours for an example of repeatable values. Example

Number of Coffee Beverages Served 12

Price for a Large Coffee Definition: the cost of a large coffee with the shop’s definition of large in fluid ounces. Instruction: the cost of the coffee may be found on the menu or from purchase. Include the tax, which is $0.08 if the cost is based on a menu price. The price should be followed by the number of fluid ounces are in a large coffee. Controlled Vocabulary: N/A Format: $#.##, # oz Repeatable: Yes. When the price or amount changes the values shift into a subcategory with the last date of entry at the beginning of the list. See Hours for an example of repeatable values. Example

Price for a Large Coffee $2.97, 16oz

Sandra Sweat -‐ 7

Food Definition: food that supports sustained time at the shop. Instruction: this information may be found on the menu in the shop or on the shop’s website. Food should not be in the form of an entree (main item and sides or a self-contained bowl such as bibimbap). Acceptable options are included in the controlled vocabulary. Only list the term, not the items included. Controlled Vocabulary:

none: no food offered. breakfast: tacos, pastries, oatmeal. snacks: nuts, fruits, chips, nutrition bars. light meal: piece of pizza, sandwiches, salad, slice of quiche.

Format: term, … , term Repeatable: Yes. When food changes the values shift into a subcategory with the last date of entry at the beginning of the list. See Hours for an example of repeatable values. Example

Food breakfast, snacks, light meal Alcohol Definition: beverages that contain alcohol. Instruction: identify the types of alcohol served. Controlled Vocabulary: none, wine, beer. Format: term, term Repeatable: Yes. When the alcohol availability and options changes the values shift into a subcategory with the last date of entry at the beginning of the list. See Hours for an example of repeatable values. Example

Alcohol beer

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Building Type Definition: the type of structure the coffee shop does business. Instruction: based on the appearance of the building, describe according to the controlled values. Only list the value, not the description. Controlled Vocabulary:

converted house: a structure that once served as a family dwelling, converted for business use. strip mall: conjoined business that share one or both walls. office building: primary purpose of the building is for office space. retail: the coffee shop is part of a larger business, but meets the requirements of a coffee shop.

Examples include grocery stores and department stores, bookstores, and the airport.

free standing: a structure that does not share walls with other businesses and is not a converted house.

Format: term Repeatable: no. Example

Building Type converted house

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WiFi Definition: wireless internet capabilities in the shop. Instruction: during the site visit, what kind of internet options are available when connecting to the internet. Controlled Vocabulary:

none: no WiFi available. sign-on: a window pops up notifying you that you are on the WiFi network of the coffee shop. code-based: a code is given to you at the time of purchase to access the internet. proximity-based: you can access the wireless connection from the parking lot without a password or sign-on screen.

Format: term Repeatable: Yes. When WiFi availability changes the values shift into a subcategory with the last date of entry at the beginning of the list. See Hours for an example of repeatable values. Example

WiFi proximity-based

Sandra Sweat -‐ 10

Seating

Definition: where customers can sit inside and associated flat surfaces with maximum occupancy. Instruction: observe the seating options in the coffee shop and determine which terms from the controlled vocabulary describe the seating. Also, calculate the largest group that could be accommodated based on seating arrangements. Controlled Vocabulary:

stools: a seat that one’s feet cannot reach the ground when seated. chairs: when seated, one’s feet can reach the ground. armchairs: upholstered chair. couches: seating for more than one person, upholstered. benches: seating without a back, may be upholstered or not upholstered. tables: flat surface with support such as legs or a base. counter: a flat surface that may be shared with multiple people, typically separating the main area of the shop from the food preparation area.

Format: List the types of seating followed by the largest number:

term, term … (7).

Repeatable: Yes. When seating changes the values shift into a subcategory with the last date of entry at the beginning of the list. See Hours for an example of repeatable values. Example

Seating chairs, couches, tables (8)


Outdoor Space Definition: seating options not inside the building. Instruction: list the type of space followed by the seating options after a colon. Controlled Vocabulary:

covered-patio: space with seating on a prepared surface such as a wooden deck or concrete with some sort of overhead shelter (roof, awning). patio: uncovered space with seating on a prepared surface such as a wooden deck or concrete. store-front: seating in front of the store. lawn: seating on a natural surface - dirt, grass, or rocks.

Format: term: seating_term, seating_term …; final term: seating_term… (largest group accommodated) Repeatable: Yes. When outdoor-space changes the values shift into a subcategory with the last date of entry at the beginning of the list. See Hours for an example of repeatable values. Example

Outdoor Space lawn: tables, benches (6)


Parking

Definition: the available parking options, including bike racks.

Instruction: count the spaces available in the parking lot and note the availability of bike racks or surrounding parking. In other parking instances, do not list the number of available spots, only list the term. When listing a number of spaces include the number of non-handicap spaces and handicapped spaced: Controlled Vocabulary:

lot: designated parking area that belongs to the coffee shop, the first values is the number of handicapped spaces and the second is unrestricted store parking.

meters: paid parking near the coffee shop. neighborhood: street parking available. bike rack: a dedicated area to lock bikes.

Format: lot: #, #; term; term; term

When there are more than 30 parking spaces total, input the following: lot: many. Repeatable: Yes. When parking changes the values shift into a subcategory with the last date of entry at the beginning of the list. See Hours for an example of repeatable values. Example

Parking lot: 1, 8; neighborhood; bike rack


Traffic Definition: The number of people present in the shop at a defined time. Instruction: perform a head-count during the time of attendance. All head counts must be performed during business hours. For instance, if you are in the shop at 9:20AM on Friday and you see 20 people you write Fri/9:20AM/20. Controlled Vocabulary: N/A Format: DAY/ hh:mm AM/PM: People inside the shop Repeatable: Yes. This value box may have many entries that can be averaged over time based on hour long blocks. For instance, all traffic between Fri/ 9:00AM - 9:59AM could be averaged and put into the table as Fri/ 9 AM: 25. Example

Traffic Patterns Wed/ 7:30 AM: 10

Life Definition: the establishment of the coffee shop through the end of the coffee shop’s life. Instruction: determine when the coffee shop started business as a coffee shop and when it ceased to operate as a coffee shop. Events that qualify for an end of life include: changing names or shifts focus to food rather than coffee. In the case the coffee shop changes names a new entry must be made for the new name. If the coffee shop does not have an establishment data on the website, search for establishment dates online or ask an employee. If the coffee shop still operates as a coffee shop do not enter an end date. Controlled Vocabulary: N/A Format: YYYY - or YYYY-YYYY Repeatable: No. Example

Life 2007 -


Created Definition: when the schema entry occurs. Instruction: This input must occur every time someone records information. Controlled Vocabulary: N/A Format: YYYY-MM-DD Repeatable: Yes. When new information is added into a repeatable category, the old date shifts to information that changed. Example

Created 2015-02-15


Examples

Thunderbird – a coffee shop with multiple locations

Name Thunderbird - Manor

Address 2200 Manor Rd., 78722



12

Price for a Large Coffee

$2.97, 16oz

Food breakfast, snacks, light meal

Alcohol beer


Wifi proximity-based


Outdoor Space lawn: tables, benches


Traffic Patterns Wed/ 7:30AM : 10

Life 2009 -

Created 2015-02-15


Clementine – a coffee shop that changed names, see previous entry, Thunderbird - Manor

Name Clementine Coffee Bar

Address 2200 Manor Road, 78722

Hours Mon/07:00 AM-11:00 PM, Tue/07:00 AM-11:00 PM, Wed07:00 AM-11:00 PM, Thurs/07:00 AM-11:00 PM, Fri/07:00 AM-11:00 PM, Sat/08:00 AM-11:00 PM, Sun/08:00 AM-10:00 PM


12


$2.15, 16oz

Food breakfast, snacks, light meals

Alcohol Beer


Wifi proximity


Outdoor Space lawn: tables, benches


Traffic Patterns 2008-01-03: Sun/ 05:57 PM: 60

Life 2005 - 2009

Created 2015-02-19


Whole Foods – shop within a retail location.

Name Whole Foods - North Lamar

Address 525 North Lamar Blvd, 78703



16


$2.70, 20 oz

Food none

Alcohol none

Building Type retail

Wifi proximity-based

Seating stools, counter, tables, chairs (12)

Outdoor Space patio: tables, benches, chairs; store-front: tables, chairs; covered-patio: chairs, tables (6)

Parking lot: many; bike rack

Traffic Patterns Sun/ 05:57 PM: 60

Life 2005 -

Created 2015-02-22


Coffee People – shop within a retail location

Name Coffee People

Address 603 N Lamar Blvd, 78703



14


$1.87, 12 oz

Food breakfast, snacks, light meal

Alcohol none

Building Type retail

Wifi code-based

Seating chairs, stools, counter, tables (6)

Outdoor Space none

Parking lot: many; bike rack

Traffic Patterns Sun/ 06:15PM: 14

Life 1997 -

Created 2015-02-22


Bennu – free-standing single location shop.

Name Bennu

Address 2001 E Martin Luther King Jr Blvd, 78702

Hours 24 hours/7days


27


$2.16, 16oz

Food breakfast, snacks, light meals

Alcohol none

Building Type free standing

Wifi proximity

Seating stools, chairs, armchairs, couches, benches, tables, counter (8)

Outdoor Space patio: tables, chairs (5)


Traffic Patterns Mon/ 11:28AM: 29

Life 2009

Created 2015-02-22


Critical Reflection

At the end of the process of writing the schema, I want to recall that “the computer will

ship without the technical instructions” (M. Feinberg, 2014). One of the most important lessons

I learned from the process of writing a technical set of instructions is determining format across

attributes early in the process. It was very helpful to look at the schemas presented in class such

as the Dublin Core when developing a structured document.

To begin, I started with one format in one section and a different format for a similar

entry, which became confusing when I made new entries and refined previous entries. It became

obvious rather quickly that one change affected the rest of the attributes. For example, I changed

the seating format from ‘term: largest group’ to ‘term (largest group)’. This change made it

necessary to change other formats with similar information to the same format for consistency

across attributes. Additionally, I wanted to put the format in such a way that it could be grouped

together later by an automated process.

A particularly surprising process was how the schema’s scope changed during the

process. I first started by using a top-down design with an idea that coffee houses were places to

not only study but also engage in leisure. I considered what I believed to be the most salient

attributes considering a broad view of what a coffee shop could include. However, when I

started defining attributes, I realized study and leisure were two separate uses with different

goals. The study group may want to spend time after group work chatting or having a beer, but

the studiers came to the coffee shop with the intent to get work done. Therefore leisure activities

become secondary and limited to only one attribute.

Considering border cases also helped define the schema’s scope and select attributes. I

originally made a list of places that I knew and considered coffee shops. However, upon further


evaluation I realized that the coffee shop community in Austin has different flavors to suit leisure

and study. For instance, I originally considered Spider House Coffee a prime example of an

Austin coffee shop. When I tried to describe it according to the schema with the audience in

mind, I discovered that Spider House provides more services that contribute to leisure than to

study because it has a full bar and extensive menu options. Spider House changed from a central

case to a starting point for defining restrictions on what is a coffee shop.

Other border cases included coffee shops that are part of other retail ventures. I wanted

to include Whole Food’s Coffee Bar because it has the elements of a coffee shop according to

the schema, but it did not meet the requirement of being in an independent space. I had to adjust

the schema to allow for coffee shops that are part of a business but run semi-independently.

Using the border case helped me define what a coffee shop is for the independent spaces as well.

For instance, I considered the role of the barista and the availability of other goods and services

offered by coffee shops. In a location like Quack’s, the barista serves coffee and the counter has

a dedicated cash register. However, the barista at Quack’s is also responsible for serving and

answering questions about baked goods and taking orders for the bakery service that Quack’s

offers. The dual role of the barista and the focus on baked goods excludes the business from the

schema.

One of the most helpful activities for creating the schema was discussing it with the class

groups. I think it was helpful for a number of reasons. First, everyone in the group had the same

goal of creating a schema, so they understood the concepts and lent advice based on their

creation experiences. Second, the group was able to suggest attributes based on the intended

audience. For instance, the group pointed out that parking and serving alcohol determines where


they go for different group and individual activities. I had not considered these attributes

because I typically ride my bike and tend not to drink beer or wine at coffee shops.

From the experiences described for this project, I have a list of things that I would want

to do in the future. First, I would want to make a rough sketch of the entity and outline the

central case and work with a border case first. I would want to do this to determine how to

include border cases in the definition of the entity. Also, when working from the border cases to

the central case, the central case may change or no longer belong in the schema. Second,

discussion with experts and indexers is helpful early in the project. After the schema has a

purpose, it helps to have others evaluate what they find important based on their personal

experiences with the scope and the audience. Third, determine format for value entry early in the

process. After the initial evaluation, determining how the schema values need to be entered for

consistency helps (for example) entry and readability. Finally, continuous testing during

creation helps refine the definition of the schema entity and attributes.

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